Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran

This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM...

Full description

Saved in:
Bibliographic Details
Published inEnergy (Oxford) Vol. 35; no. 12; pp. 5223 - 5229
Main Authors Assareh, E., Behrang, M.A., Assari, M.R., Ghanbarzadeh, A.
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.12.2010
Elsevier
Subjects
Applied sciences
Demand
Domestic
Economic data
Energy
Energy economics
Estimates
Exact sciences and technology
Exports
Fossil fuels and derived products
GA (genetic algorithm)
General, economic and professional studies
Genetic algorithms
Marketing
Mathematical models
Methodology. Modelling
Oil
Optimization
Projection
PSO (particle swarm optimization)
Iran
Asia
Demand
PSO (particle swarm optimization)
Projection
Oil
GA (genetic algorithm)
Genetic algorithm
Socioeconomic study
Long term
Modeling
Particle swarm optimization
Forecasting
Petroleum
Online AccessGet full text

Cover

Abstract This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA–DEMexponential and GA–DEMlinear, respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO–DEMexponential and PSO–DEMlinear, respectively. Oil demand in Iran is forecasted up to year 2030.
AbstractList This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA–DEMexponential and GA–DEMlinear, respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO–DEMexponential and PSO–DEMlinear, respectively. Oil demand in Iran is forecasted up to year 2030.
This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO-DEM and GA-DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981-1999) and partly for testing the models (2000-2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA-DEM sub(exponential) and GA-DEM sub(linear), respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO-DEM sub(exponential) and PSO-DEM sub(linear), respectively. Oil demand in Iran is forecasted up to year 2030.
Author Behrang, M.A.
Assari, M.R.
Ghanbarzadeh, A.
Assareh, E.
Author_xml – sequence: 1
  givenname: E.
  surname: Assareh
  fullname: Assareh, E.
  email: Ehsanolah.Assareh@gmail.com
  organization: Department of Mechanical Engineering, Young Researchers Club, Islamic Azad University, Dezful Branch, Iran
– sequence: 2
  givenname: M.A.
  surname: Behrang
  fullname: Behrang, M.A.
  organization: Department of Mechanical Engineering, Young Researchers Club, Islamic Azad University, Dezful Branch, Iran
– sequence: 3
  givenname: M.R.
  surname: Assari
  fullname: Assari, M.R.
  organization: Department of Mechanical Engineering, Engineering Faculty, Jundi Shapour University, Dezful, Iran
– sequence: 4
  givenname: A.
  surname: Ghanbarzadeh
  fullname: Ghanbarzadeh, A.
  organization: Department of Mechanical Engineering, Engineering Faculty, Shahid Chamran University, Ahvaz, Iran
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23651525$$DView record in Pascal Francis
BookMark eNp9kEtLAzEUhbOo4PMfuMhG1EXrzWQyj41QxBcICuo6ZJI7NWUmGZNRqb_e1BaXrnIJ3znn3rNPJs47JOSYwYwBKy6WM3QYFqtZBukLyhnkfEL2gBcwFXme7ZL9GJcAIKq63iPf82HorFaj9Y76lj49P9KzQYXR6g5p_FKhp34YbW-_f5lzqpyht3N6tkg5iaKqW_hgx7f-nI6o35x9_8BIk5vBfs1iTOo_f287ah29D8odkp1WdRGPtu8Beb25frm6mz483t5fzR-mOuf5OG1LrBrIUFcMGqFK1bSsFigMFGlsjWh4K-oKBCsKlpmmMiUvtKpqDZybrOQH5HTjOwS_3m2UvY0au0459B9RVkKUybHmicw3pA4-xoCtHELaPawkA7luVy7lpl25bldCKVO7SXayDVBRq65Nt2kb_7QZLwQTmUjc5YbDdO2nxSCjtug0GhtQj9J4-3_QDzcDlwY
CODEN ENEYDS
CitedBy_id crossref_primary_10_3390_su13147612
crossref_primary_10_2166_nh_2017_206
crossref_primary_10_1016_j_petlm_2017_06_001
crossref_primary_10_1016_j_energy_2012_10_030
crossref_primary_10_1016_j_jclepro_2020_125287
crossref_primary_10_1016_j_energy_2018_03_120
crossref_primary_10_1007_s00521_014_1766_y
crossref_primary_10_1007_s00500_021_06095_4
crossref_primary_10_1016_j_enbuild_2015_11_043
crossref_primary_10_1016_j_ijepes_2013_08_017
crossref_primary_10_1007_s00521_017_3244_9
crossref_primary_10_1007_s10706_018_0570_3
crossref_primary_10_1016_j_energy_2013_12_043
crossref_primary_10_1016_j_energy_2017_03_009
crossref_primary_10_1109_TII_2017_2786782
crossref_primary_10_1016_j_jclepro_2023_139207
crossref_primary_10_1166_jctn_2020_9239
crossref_primary_10_1061__ASCE_CP_1943_5487_0000354
crossref_primary_10_55195_jscai_1401378
crossref_primary_10_1016_j_petrol_2019_106187
crossref_primary_10_1016_j_knosys_2022_108687
crossref_primary_10_1007_s13369_018_3383_z
crossref_primary_10_1016_j_rser_2018_02_002
crossref_primary_10_1109_ACCESS_2020_2990439
crossref_primary_10_1007_s40095_015_0179_8
crossref_primary_10_1002_acs_2320
crossref_primary_10_1016_j_eswa_2021_115376
crossref_primary_10_1002_etep_2645
crossref_primary_10_1016_j_molliq_2020_114468
crossref_primary_10_1016_j_enconman_2011_08_015
crossref_primary_10_1007_s41605_021_00248_7
crossref_primary_10_3390_app8010003
crossref_primary_10_1080_15567036_2010_493920
crossref_primary_10_1016_j_energy_2011_02_048
crossref_primary_10_1002_cjce_24159
crossref_primary_10_1007_s00500_023_08676_x
crossref_primary_10_1016_j_ces_2022_117533
crossref_primary_10_3390_en11040728
crossref_primary_10_1016_j_powtec_2016_08_027
crossref_primary_10_1142_S0219622016500097
crossref_primary_10_1007_s11069_019_03688_z
crossref_primary_10_1080_15567036_2011_551915
crossref_primary_10_1002_met_1841
crossref_primary_10_1007_s42979_022_01208_8
crossref_primary_10_1016_j_energy_2014_03_059
crossref_primary_10_1016_j_anucene_2021_108375
crossref_primary_10_1016_j_asoc_2013_06_024
crossref_primary_10_3390_en14237919
crossref_primary_10_1016_j_eswa_2020_113268
crossref_primary_10_1155_2022_8412895
crossref_primary_10_3390_en14164890
crossref_primary_10_1016_j_ins_2018_01_041
crossref_primary_10_1007_s00202_024_02364_1
crossref_primary_10_1016_j_energy_2014_05_022
crossref_primary_10_1016_j_energy_2019_07_154
crossref_primary_10_1109_ACCESS_2018_2838596
crossref_primary_10_1007_s00521_023_08769_6
crossref_primary_10_1016_j_ijforecast_2017_11_005
crossref_primary_10_2478_jamsi_2022_0011
crossref_primary_10_1016_j_enconman_2011_08_004
crossref_primary_10_24017_Science_2022_2_5
crossref_primary_10_1057_s41599_020_0465_9
crossref_primary_10_1080_23311916_2020_1737383
crossref_primary_10_1016_j_energy_2015_10_015
crossref_primary_10_1080_15567240903394265
crossref_primary_10_1177_03019233241247397
crossref_primary_10_3390_en14164804
crossref_primary_10_1177_01445987221107679
crossref_primary_10_1117_1_JEI_28_3_033036
crossref_primary_10_1007_s11771_019_4161_0
crossref_primary_10_3390_en12142807
crossref_primary_10_1002_ese3_849
crossref_primary_10_1016_j_applthermaleng_2017_10_134
crossref_primary_10_1021_acs_iecr_0c05143
crossref_primary_10_1007_s10462_018_9612_8
crossref_primary_10_1088_1742_6596_1805_1_012031
crossref_primary_10_1016_j_energy_2017_03_094
crossref_primary_10_1108_GS_09_2022_0100
crossref_primary_10_1002_kin_21577
crossref_primary_10_1007_s11069_020_04067_9
crossref_primary_10_1080_10042857_2015_1111572
crossref_primary_10_1016_j_resourpol_2013_09_007
crossref_primary_10_1007_s00521_016_2182_2
crossref_primary_10_1016_j_mex_2021_101226
crossref_primary_10_3390_math11091977
crossref_primary_10_1016_j_energy_2012_08_013
crossref_primary_10_1364_AO_54_000037
crossref_primary_10_1007_s13201_022_01815_z
crossref_primary_10_1007_s13369_021_05705_5
crossref_primary_10_1155_2020_1365195
crossref_primary_10_1021_acs_iecr_3c02254
crossref_primary_10_1007_s11269_020_02619_z
crossref_primary_10_1016_j_mri_2019_12_012
crossref_primary_10_1016_j_aci_2017_09_006
crossref_primary_10_1021_acsomega_3c05054
crossref_primary_10_1016_j_apenergy_2018_05_033
crossref_primary_10_1016_j_energy_2013_04_007
crossref_primary_10_3103_S0146411619050092
crossref_primary_10_1108_CI_11_2017_0089
crossref_primary_10_1016_j_ijfatigue_2024_108321
crossref_primary_10_1080_15567241003792341
crossref_primary_10_1080_15567240903502594
crossref_primary_10_1080_15567036_2011_601798
crossref_primary_10_1155_2019_8251829
crossref_primary_10_1155_2016_7912357
crossref_primary_10_1007_s40846_017_0306_5
crossref_primary_10_1007_s40092_017_0240_8
crossref_primary_10_3390_en13020305
crossref_primary_10_1111_ffe_13343
crossref_primary_10_4236_jcc_2014_24015
crossref_primary_10_1108_IJESM_10_2014_0006
crossref_primary_10_4018_IJCINI_2019040102
crossref_primary_10_1021_ie3022169
crossref_primary_10_1016_j_enpol_2011_11_090
crossref_primary_10_1016_j_psep_2021_12_006
crossref_primary_10_1155_2014_414058
crossref_primary_10_1016_j_energy_2019_116045
crossref_primary_10_1142_S0218001419590419
crossref_primary_10_1016_j_energy_2016_05_029
crossref_primary_10_1007_s00500_012_0855_z
crossref_primary_10_1007_s13202_016_0229_7
crossref_primary_10_1016_j_energy_2011_11_015
crossref_primary_10_1016_j_fuel_2016_05_124
crossref_primary_10_31127_tuje_1354501
crossref_primary_10_1155_2021_6189329
crossref_primary_10_1007_s10489_018_1364_2
crossref_primary_10_1016_j_petrol_2021_108368
crossref_primary_10_18201_ijisae_266082
crossref_primary_10_1016_j_enconman_2011_11_013
crossref_primary_10_1080_02626667_2021_1985123
crossref_primary_10_1109_TCBB_2021_3103777
crossref_primary_10_1016_j_rser_2016_06_034
crossref_primary_10_1016_j_scs_2021_102936
crossref_primary_10_1002_cpe_2957
crossref_primary_10_1016_j_energy_2022_123735
crossref_primary_10_1007_s13042_021_01345_1
crossref_primary_10_1155_2019_5213759
crossref_primary_10_1016_j_energy_2020_119720
crossref_primary_10_1016_j_apenergy_2015_03_079
crossref_primary_10_1016_j_energy_2011_07_002
crossref_primary_10_1016_j_energy_2016_09_015
crossref_primary_10_1016_j_asoc_2016_06_038
crossref_primary_10_1061__ASCE_BE_1943_5592_0001130
crossref_primary_10_1016_j_asoc_2014_05_033
crossref_primary_10_1016_j_apenergy_2016_12_034
crossref_primary_10_1016_j_energy_2014_05_070
crossref_primary_10_1007_s12665_015_5221_x
crossref_primary_10_1155_2019_5052185
crossref_primary_10_1016_j_amc_2015_08_085
crossref_primary_10_3390_s22031008
crossref_primary_10_1016_j_jestch_2016_10_012
crossref_primary_10_17780_ksujes_1200583
Cites_doi 10.1016/j.energy.2007.12.008
10.1016/j.advengsoft.2006.10.009
10.1109/TSMC.1986.289288
10.1016/j.ijproman.2006.11.001
10.1016/j.enpol.2008.02.018
10.1016/j.energy.2010.06.010
10.1016/j.energy.2008.09.020
10.1016/j.energy.2010.03.043
10.1016/j.enpol.2008.03.014
10.1016/j.energy.2006.03.021
10.1016/j.energy.2009.12.023
10.1016/j.enconman.2009.10.013
10.1016/j.energy.2009.12.025
10.1016/B978-0-08-050684-5.50008-2
10.1016/j.enpol.2007.01.028
10.1016/j.amc.2006.01.066
10.1016/j.energy.2006.11.014
10.1016/j.energy.2010.01.017
10.1016/j.energy.2009.06.032
10.1016/j.enpol.2007.04.031
10.1016/B978-0-08-050684-5.50009-4
10.1016/j.energy.2009.10.018
10.1016/j.enpol.2008.03.010
10.1016/j.energy.2008.05.008
10.1016/j.amc.2006.12.066
10.1109/ICEC.1997.592270
10.1162/evco.1993.1.1.51
10.1109/ICNN.1995.488968
10.1109/ICEC.1998.699146
10.1016/j.rser.2004.03.002
10.1016/j.enpol.2008.02.035
10.1007/BFb0040810
ContentType Journal Article
Copyright 2010 Elsevier Ltd
2015 INIST-CNRS
Copyright_xml – notice: 2010 Elsevier Ltd
– notice: 2015 INIST-CNRS
DBID IQODW
AAYXX
CITATION
7SP
7TB
8FD
F28
FR3
KR7
L7M
DOI 10.1016/j.energy.2010.07.043
DatabaseName Pascal-Francis
CrossRef
Electronics & Communications Abstracts
Mechanical & Transportation Engineering Abstracts
Technology Research Database
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
Civil Engineering Abstracts
Advanced Technologies Database with Aerospace
DatabaseTitle CrossRef
Civil Engineering Abstracts
Technology Research Database
Mechanical & Transportation Engineering Abstracts
Electronics & Communications Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
ANTE: Abstracts in New Technology & Engineering
DatabaseTitleList
Civil Engineering Abstracts
DeliveryMethod fulltext_linktorsrc
Discipline Economics
Environmental Sciences
Applied Sciences
EndPage 5229
ExternalDocumentID 10_1016_j_energy_2010_07_043
23651525
S0360544210004184
GeographicLocations Iran
Asia
GroupedDBID --K
--M
.DC
.~1
0R~
1B1
1RT
1~.
1~5
29G
4.4
457
4G.
5GY
5VS
6TJ
7-5
71M
8P~
9JN
AABNK
AACTN
AAEDT
AAEDW
AAHCO
AAIAV
AAIKC
AAIKJ
AAKOC
AALRI
AAMNW
AAOAW
AAQFI
AAQXK
AARJD
AAXUO
ABFNM
ABJNI
ABMAC
ABXDB
ABYKQ
ACDAQ
ACGFS
ACIWK
ACRLP
ADBBV
ADEZE
ADMUD
AEBSH
AEKER
AENEX
AFKWA
AFRAH
AFTJW
AGHFR
AGUBO
AGYEJ
AHHHB
AHIDL
AIEXJ
AIKHN
AITUG
AJBFU
AJOXV
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
ASPBG
AVWKF
AXJTR
AZFZN
BELTK
BKOJK
BLXMC
CS3
DU5
EBS
EFJIC
EFLBG
EJD
EO8
EO9
EP2
EP3
FDB
FEDTE
FGOYB
FIRID
FNPLU
FYGXN
G-2
G-Q
G8K
GBLVA
HVGLF
HZ~
IHE
J1W
JARJE
KOM
LY6
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
Q38
R2-
RIG
RNS
ROL
RPZ
SAC
SDF
SDG
SES
SEW
SPC
SPCBC
SSR
SSZ
T5K
TN5
WUQ
XPP
ZMT
~02
~G-
ABPIF
ABPTK
IQODW
AAHBH
AAXKI
AAYXX
ABDPE
ACRPL
AFJKZ
AKRWK
CITATION
7SP
7TB
8FD
F28
FR3
KR7
L7M
ID FETCH-LOGICAL-c434t-f7e8b02ec810b5a7abf195e5d06abffd5b3f5980516612db8d736ca89c033d273
IEDL.DBID AIKHN
ISSN 0360-5442
IngestDate Wed Dec 04 15:39:40 EST 2024
Fri Dec 06 00:47:24 EST 2024
Sun Oct 22 16:07:38 EDT 2023
Fri Feb 23 02:16:17 EST 2024
IsPeerReviewed true
IsScholarly true
Issue 12
Keywords Demand
PSO (particle swarm optimization)
Projection
Oil
GA (genetic algorithm)
Genetic algorithm
Socioeconomic study
Long term
Modeling
Particle swarm optimization
Forecasting
Petroleum
Language English
License CC BY 4.0
https://www.elsevier.com/tdm/userlicense/1.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c434t-f7e8b02ec810b5a7abf195e5d06abffd5b3f5980516612db8d736ca89c033d273
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PQID 855719593
PQPubID 23500
PageCount 7
ParticipantIDs proquest_miscellaneous_855719593
crossref_primary_10_1016_j_energy_2010_07_043
pascalfrancis_primary_23651525
elsevier_sciencedirect_doi_10_1016_j_energy_2010_07_043
PublicationCentury 2000
PublicationDate 2010-12-01
PublicationDateYYYYMMDD 2010-12-01
PublicationDate_xml – month: 12
  year: 2010
  text: 2010-12-01
  day: 01
PublicationDecade 2010
PublicationPlace Kidlington
PublicationPlace_xml – name: Kidlington
PublicationTitle Energy (Oxford)
PublicationYear 2010
Publisher Elsevier Ltd
Elsevier
Publisher_xml – name: Elsevier Ltd
– name: Elsevier
References Amarawickrama, Hunt (bib13) 2008; 33
Zhang, Mu, Li, Ning (bib11) 2009; 34
Goldberg, Deb (bib29) 1991
Karbassi, Abduli, Mahin Abdollahzadeh (bib3) 2007; 35
Baker JE. Adaptive selection methods for genetic algorithms. In: Proceedings of Int. Conf. on genetic algorithms and their applications; 1985. p. 101–11.
Amjady, Keynia (bib20) 2009; 34
Shi Y, Eberhart R. Parameter selection in particle swarm optimization. In: Proceedings of the Seventh Annual conference on evolutionary programming. New York; 1998. p. 591–600.
Brits, Engelbrecht, van den Bergh (bib37) 2007; 189
Michalewicz (bib25) 1999
Nava, Gasca, Gonzalez (bib12) 2006; 31
Holland (bib22) 1975
Akay, Atak (bib16) 2007; 32
Michalewicz (bib34) 1993; 1
Syswerda (bib27) 1991
Pappas, Ekonomou, Karamousantas, Chatzarakis, Katsikas, Liatsis (bib21) 2008; 33
Back T. Optimal mutation rates in genetic search. In: Proc fifth Int. Conf. on genetic algorithm. San Mateo: Morgan Kaufmann, 1993. p. 2–9.
Schaffer JD, Caruana RA, Eshelman LJ, Das R. A study of control parameters affecting online performance of genetic algorithms for function optimization. In: Proceedings of the Third international conference on Genetic algorithms: Morgan Kaufmann, San Francisco, CA; 1989. p. 51–60.
Engelbrecht (bib36) 2005
Grefenstette JJ, Baker JE. How genetic algorithms work: A critical look at implicit parallelism. In: Proceedings of the third Int. Conf. on Genetic Algorithms; 1989. p. 20–7.
Yang (bib40) 2007; 25
Azadeh, Ghaderi, Sohrabkhani (bib8) 2008; 36
Goldberg (bib23) 1989
Amjadi, Nezamabadi-pour, Farsangi (bib10) 2010; 51
Shi Y, Eberhart R. A modified particle swarm optimizer. In: Proceedings of the IEEE international conference on evolutionary computation. Anchorage, Alaska; 1998. p. 69–73.
Canyurt, Ozturk (bib6) 2008; 36
Unler (bib5) 2008; 36
Davis (bib26) 1991
Hessari (bib4) 2005; 9
Askari, Krichene (bib14) 2010; 35
Kennedy J, Eberhart R. Particle swarm optimization. Proc Neural Networks. In: Proceedings of IEEE International Conference on vol. 1944; 1995. p. 1942–8.
Azadeh, Saberi, Seraj (bib9) 2010; 35
Energy Balance Annual Report (bib2) 2005
Cinar, Kayakutlu, Daim (bib15) 2010; 35
Ekonomou (bib17) 2010; 35
Hinterding R, Michalewicz Z, Eiben AE. Adaptation in evolutionary computation: a survey. In: Proc IEEE international conference on evolutionary computation; 1997. p. 65–9.
Liu, Liu, Duan (bib38) 2007; 38
Pan, Wang, Liu (bib39) 2006; 181
Grefenstette (bib30) 1986; 16
Tang, Zhang, Hook, Feng (bib19) 2010; 35
Toksari (bib7) 2007; 35
Jovanovic, Afgan, Bakic (bib18) 2010; 35
Houri Jafari, Baratimalayeri (bib1) 2008; 36
Canyurt (10.1016/j.energy.2010.07.043_bib6) 2008; 36
Azadeh (10.1016/j.energy.2010.07.043_bib9) 2010; 35
Pan (10.1016/j.energy.2010.07.043_bib39) 2006; 181
Michalewicz (10.1016/j.energy.2010.07.043_bib34) 1993; 1
10.1016/j.energy.2010.07.043_bib41
10.1016/j.energy.2010.07.043_bib42
Tang (10.1016/j.energy.2010.07.043_bib19) 2010; 35
10.1016/j.energy.2010.07.043_bib28
Ekonomou (10.1016/j.energy.2010.07.043_bib17) 2010; 35
10.1016/j.energy.2010.07.043_bib24
Grefenstette (10.1016/j.energy.2010.07.043_bib30) 1986; 16
Hessari (10.1016/j.energy.2010.07.043_bib4) 2005; 9
Amarawickrama (10.1016/j.energy.2010.07.043_bib13) 2008; 33
Syswerda (10.1016/j.energy.2010.07.043_bib27) 1991
Engelbrecht (10.1016/j.energy.2010.07.043_bib36) 2005
Karbassi (10.1016/j.energy.2010.07.043_bib3) 2007; 35
Liu (10.1016/j.energy.2010.07.043_bib38) 2007; 38
Goldberg (10.1016/j.energy.2010.07.043_bib23) 1989
10.1016/j.energy.2010.07.043_bib32
Amjadi (10.1016/j.energy.2010.07.043_bib10) 2010; 51
Amjady (10.1016/j.energy.2010.07.043_bib20) 2009; 34
10.1016/j.energy.2010.07.043_bib33
10.1016/j.energy.2010.07.043_bib31
Yang (10.1016/j.energy.2010.07.043_bib40) 2007; 25
Unler (10.1016/j.energy.2010.07.043_bib5) 2008; 36
Energy Balance Annual Report (10.1016/j.energy.2010.07.043_bib2) 2005
Michalewicz (10.1016/j.energy.2010.07.043_bib25) 1999
Goldberg (10.1016/j.energy.2010.07.043_bib29) 1991
Azadeh (10.1016/j.energy.2010.07.043_bib8) 2008; 36
Cinar (10.1016/j.energy.2010.07.043_bib15) 2010; 35
Brits (10.1016/j.energy.2010.07.043_bib37) 2007; 189
Toksari (10.1016/j.energy.2010.07.043_bib7) 2007; 35
Jovanovic (10.1016/j.energy.2010.07.043_bib18) 2010; 35
Pappas (10.1016/j.energy.2010.07.043_bib21) 2008; 33
Holland (10.1016/j.energy.2010.07.043_bib22) 1975
10.1016/j.energy.2010.07.043_bib35
Houri Jafari (10.1016/j.energy.2010.07.043_bib1) 2008; 36
Askari (10.1016/j.energy.2010.07.043_bib14) 2010; 35
Davis (10.1016/j.energy.2010.07.043_bib26) 1991
Nava (10.1016/j.energy.2010.07.043_bib12) 2006; 31
Zhang (10.1016/j.energy.2010.07.043_bib11) 2009; 34
Akay (10.1016/j.energy.2010.07.043_bib16) 2007; 32
References_xml – year: 2005
  ident: bib36
  article-title: Fundamentals of computational swarm intelligence
  contributor:
    fullname: Engelbrecht
– volume: 36
  start-page: 2536
  year: 2008
  end-page: 2543
  ident: bib1
  article-title: The crisis of gasoline consumption in the Iran’s transportation sector
  publication-title: Energy Policy
  contributor:
    fullname: Baratimalayeri
– volume: 25
  start-page: 637
  year: 2007
  end-page: 646
  ident: bib40
  article-title: Performing complex project crashing analysis with aid of particle swarm optimization algorithm
  publication-title: International Journal of Project Management
  contributor:
    fullname: Yang
– year: 2005
  ident: bib2
  contributor:
    fullname: Energy Balance Annual Report
– volume: 9
  start-page: 203
  year: 2005
  end-page: 214
  ident: bib4
  article-title: Sectoral energy consumption in Iran
  publication-title: Renewable and Sustainable Energy Reviews
  contributor:
    fullname: Hessari
– year: 1999
  ident: bib25
  article-title: Genetic algorithms + data structures = evolution programs
  contributor:
    fullname: Michalewicz
– volume: 35
  start-page: 3984
  year: 2007
  end-page: 3990
  ident: bib7
  article-title: Ant colony optimization approach to estimate energy demand in Turkey
  publication-title: Energy Policy
  contributor:
    fullname: Toksari
– volume: 33
  start-page: 724
  year: 2008
  end-page: 739
  ident: bib13
  article-title: Electricity demand for Sri Lanka: a time series analysis
  publication-title: Energy
  contributor:
    fullname: Hunt
– volume: 35
  start-page: 3097
  year: 2010
  end-page: 3102
  ident: bib19
  article-title: Forecast of oil reserves and production in Daqing oilfield of China
  publication-title: Energy
  contributor:
    fullname: Feng
– volume: 38
  start-page: 668
  year: 2007
  end-page: 676
  ident: bib38
  article-title: Particle swarm optimization based on dynamic niche technology with applications to conceptual design
  publication-title: Advances in Engineering Software
  contributor:
    fullname: Duan
– volume: 35
  start-page: 2351
  year: 2010
  end-page: 2366
  ident: bib9
  article-title: An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: a case study of Iran
  publication-title: Energy
  contributor:
    fullname: Seraj
– volume: 36
  start-page: 1937
  year: 2008
  end-page: 1944
  ident: bib5
  article-title: Improvement of energy demand forecasts using swarm intelligence: the case of Turkey with projections to 2025
  publication-title: Energy Policy
  contributor:
    fullname: Unler
– volume: 35
  start-page: 512
  year: 2010
  end-page: 517
  ident: bib17
  article-title: Greek long-term energy consumption prediction using artificial neural networks
  publication-title: Energy
  contributor:
    fullname: Ekonomou
– volume: 35
  start-page: 2013
  year: 2010
  end-page: 2021
  ident: bib14
  article-title: An oil demand and supply model incorporating monetary policy
  publication-title: Energy
  contributor:
    fullname: Krichene
– volume: 36
  start-page: 2562
  year: 2008
  end-page: 2569
  ident: bib6
  article-title: Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey
  publication-title: Energy Policy
  contributor:
    fullname: Ozturk
– volume: 33
  start-page: 1353
  year: 2008
  end-page: 1360
  ident: bib21
  article-title: Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models
  publication-title: Energy
  contributor:
    fullname: Liatsis
– volume: 34
  start-page: 46
  year: 2009
  end-page: 57
  ident: bib20
  article-title: Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm
  publication-title: Energy
  contributor:
    fullname: Keynia
– volume: 1
  start-page: 51
  year: 1993
  end-page: 76
  ident: bib34
  article-title: A hierarchy of evolution programs: an experimental study
  publication-title: Evolutionary Computation
  contributor:
    fullname: Michalewicz
– volume: 51
  start-page: 493
  year: 2010
  end-page: 497
  ident: bib10
  article-title: Estimation of electricity demand of Iran using two heuristic algorithms
  publication-title: Energy Conversion and Management
  contributor:
    fullname: Farsangi
– volume: 35
  start-page: 3909
  year: 2010
  end-page: 3920
  ident: bib18
  article-title: An analytical method for the measurement of energy system sustainability in urban areas
  publication-title: Energy
  contributor:
    fullname: Bakic
– year: 1991
  ident: bib26
  article-title: Handbook of genetic algorithms
  contributor:
    fullname: Davis
– volume: 189
  start-page: 1859
  year: 2007
  end-page: 1883
  ident: bib37
  article-title: Locating multiple optima using particle swarm optimization
  publication-title: Applied Mathematics and Computation
  contributor:
    fullname: van den Bergh
– start-page: 69
  year: 1991
  end-page: 93
  ident: bib29
  article-title: A comparison of selection schemes used in genetic algorithms
  publication-title: Foundations of genetic algorithms (FOGA 1)
  contributor:
    fullname: Deb
– year: 1989
  ident: bib23
  article-title: Genetic algorithms in search, optimization and machine learning
  contributor:
    fullname: Goldberg
– year: 1975
  ident: bib22
  article-title: Adaptations in natural artificial systems
  contributor:
    fullname: Holland
– volume: 36
  start-page: 2637
  year: 2008
  end-page: 2644
  ident: bib8
  article-title: A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran
  publication-title: Energy Policy
  contributor:
    fullname: Sohrabkhani
– volume: 181
  start-page: 908
  year: 2006
  end-page: 919
  ident: bib39
  article-title: Particle swarm optimization for function optimization in noisy environment
  publication-title: Applied Mathematics and Computation
  contributor:
    fullname: Liu
– volume: 34
  start-page: 1396
  year: 2009
  end-page: 1400
  ident: bib11
  article-title: Forecasting the transport energy demand based on PLSR method in China
  publication-title: Energy
  contributor:
    fullname: Ning
– volume: 35
  start-page: 1724
  year: 2010
  end-page: 1729
  ident: bib15
  article-title: Development of future energy scenarios with intelligent algorithms: case of hydro in Turkey
  publication-title: Energy
  contributor:
    fullname: Daim
– volume: 32
  start-page: 1670
  year: 2007
  end-page: 1675
  ident: bib16
  article-title: Grey prediction with rolling mechanism for electricity demand forecasting of Turkey
  publication-title: Energy
  contributor:
    fullname: Atak
– volume: 35
  start-page: 5171
  year: 2007
  end-page: 5180
  ident: bib3
  article-title: Sustainability of energy production and use in Iran
  publication-title: Energy Policy
  contributor:
    fullname: Mahin Abdollahzadeh
– volume: 31
  start-page: 3381
  year: 2006
  end-page: 3390
  ident: bib12
  article-title: The energy demand and the impact by fossil fuels use in the Mexico City Metropolitan Area, from 1988 to 2000
  publication-title: Energy
  contributor:
    fullname: Gonzalez
– volume: 16
  start-page: 122
  year: 1986
  end-page: 128
  ident: bib30
  article-title: Optimization of control parameters for genetic algorithms
  publication-title: Systems, Man and Cybernetics, IEEE Transactions on
  contributor:
    fullname: Grefenstette
– start-page: 94
  year: 1991
  end-page: 101
  ident: bib27
  article-title: Reproduction in generational and steady state genetic algorithm
  publication-title: Foundations of genetic algorithms
  contributor:
    fullname: Syswerda
– volume: 33
  start-page: 724
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib13
  article-title: Electricity demand for Sri Lanka: a time series analysis
  publication-title: Energy
  doi: 10.1016/j.energy.2007.12.008
  contributor:
    fullname: Amarawickrama
– volume: 38
  start-page: 668
  issue: 10
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib38
  article-title: Particle swarm optimization based on dynamic niche technology with applications to conceptual design
  publication-title: Advances in Engineering Software
  doi: 10.1016/j.advengsoft.2006.10.009
  contributor:
    fullname: Liu
– volume: 16
  start-page: 122
  issue: 1
  year: 1986
  ident: 10.1016/j.energy.2010.07.043_bib30
  article-title: Optimization of control parameters for genetic algorithms
  publication-title: Systems, Man and Cybernetics, IEEE Transactions on
  doi: 10.1109/TSMC.1986.289288
  contributor:
    fullname: Grefenstette
– volume: 25
  start-page: 637
  issue: 6
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib40
  article-title: Performing complex project crashing analysis with aid of particle swarm optimization algorithm
  publication-title: International Journal of Project Management
  doi: 10.1016/j.ijproman.2006.11.001
  contributor:
    fullname: Yang
– volume: 36
  start-page: 1937
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib5
  article-title: Improvement of energy demand forecasts using swarm intelligence: the case of Turkey with projections to 2025
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2008.02.018
  contributor:
    fullname: Unler
– volume: 35
  start-page: 3909
  issue: 9
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib18
  article-title: An analytical method for the measurement of energy system sustainability in urban areas
  publication-title: Energy
  doi: 10.1016/j.energy.2010.06.010
  contributor:
    fullname: Jovanovic
– volume: 34
  start-page: 46
  year: 2009
  ident: 10.1016/j.energy.2010.07.043_bib20
  article-title: Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm
  publication-title: Energy
  doi: 10.1016/j.energy.2008.09.020
  contributor:
    fullname: Amjady
– ident: 10.1016/j.energy.2010.07.043_bib28
– volume: 35
  start-page: 3097
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib19
  article-title: Forecast of oil reserves and production in Daqing oilfield of China
  publication-title: Energy
  doi: 10.1016/j.energy.2010.03.043
  contributor:
    fullname: Tang
– volume: 36
  start-page: 2536
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib1
  article-title: The crisis of gasoline consumption in the Iran’s transportation sector
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2008.03.014
  contributor:
    fullname: Houri Jafari
– volume: 31
  start-page: 3381
  year: 2006
  ident: 10.1016/j.energy.2010.07.043_bib12
  article-title: The energy demand and the impact by fossil fuels use in the Mexico City Metropolitan Area, from 1988 to 2000
  publication-title: Energy
  doi: 10.1016/j.energy.2006.03.021
  contributor:
    fullname: Nava
– ident: 10.1016/j.energy.2010.07.043_bib24
– volume: 35
  start-page: 2351
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib9
  article-title: An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: a case study of Iran
  publication-title: Energy
  doi: 10.1016/j.energy.2009.12.023
  contributor:
    fullname: Azadeh
– volume: 51
  start-page: 493
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib10
  article-title: Estimation of electricity demand of Iran using two heuristic algorithms
  publication-title: Energy Conversion and Management
  doi: 10.1016/j.enconman.2009.10.013
  contributor:
    fullname: Amjadi
– volume: 35
  start-page: 1724
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib15
  article-title: Development of future energy scenarios with intelligent algorithms: case of hydro in Turkey
  publication-title: Energy
  doi: 10.1016/j.energy.2009.12.025
  contributor:
    fullname: Cinar
– start-page: 69
  year: 1991
  ident: 10.1016/j.energy.2010.07.043_bib29
  article-title: A comparison of selection schemes used in genetic algorithms
  doi: 10.1016/B978-0-08-050684-5.50008-2
  contributor:
    fullname: Goldberg
– volume: 35
  start-page: 3984
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib7
  article-title: Ant colony optimization approach to estimate energy demand in Turkey
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2007.01.028
  contributor:
    fullname: Toksari
– year: 2005
  ident: 10.1016/j.energy.2010.07.043_bib2
  contributor:
    fullname: Energy Balance Annual Report
– year: 1989
  ident: 10.1016/j.energy.2010.07.043_bib23
  contributor:
    fullname: Goldberg
– volume: 181
  start-page: 908
  issue: 2
  year: 2006
  ident: 10.1016/j.energy.2010.07.043_bib39
  article-title: Particle swarm optimization for function optimization in noisy environment
  publication-title: Applied Mathematics and Computation
  doi: 10.1016/j.amc.2006.01.066
  contributor:
    fullname: Pan
– volume: 32
  start-page: 1670
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib16
  article-title: Grey prediction with rolling mechanism for electricity demand forecasting of Turkey
  publication-title: Energy
  doi: 10.1016/j.energy.2006.11.014
  contributor:
    fullname: Akay
– volume: 35
  start-page: 2013
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib14
  article-title: An oil demand and supply model incorporating monetary policy
  publication-title: Energy
  doi: 10.1016/j.energy.2010.01.017
  contributor:
    fullname: Askari
– volume: 34
  start-page: 1396
  year: 2009
  ident: 10.1016/j.energy.2010.07.043_bib11
  article-title: Forecasting the transport energy demand based on PLSR method in China
  publication-title: Energy
  doi: 10.1016/j.energy.2009.06.032
  contributor:
    fullname: Zhang
– ident: 10.1016/j.energy.2010.07.043_bib31
– year: 2005
  ident: 10.1016/j.energy.2010.07.043_bib36
  contributor:
    fullname: Engelbrecht
– volume: 35
  start-page: 5171
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib3
  article-title: Sustainability of energy production and use in Iran
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2007.04.031
  contributor:
    fullname: Karbassi
– start-page: 94
  year: 1991
  ident: 10.1016/j.energy.2010.07.043_bib27
  article-title: Reproduction in generational and steady state genetic algorithm
  doi: 10.1016/B978-0-08-050684-5.50009-4
  contributor:
    fullname: Syswerda
– ident: 10.1016/j.energy.2010.07.043_bib33
– volume: 35
  start-page: 512
  year: 2010
  ident: 10.1016/j.energy.2010.07.043_bib17
  article-title: Greek long-term energy consumption prediction using artificial neural networks
  publication-title: Energy
  doi: 10.1016/j.energy.2009.10.018
  contributor:
    fullname: Ekonomou
– volume: 36
  start-page: 2562
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib6
  article-title: Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2008.03.010
  contributor:
    fullname: Canyurt
– volume: 33
  start-page: 1353
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib21
  article-title: Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models
  publication-title: Energy
  doi: 10.1016/j.energy.2008.05.008
  contributor:
    fullname: Pappas
– volume: 189
  start-page: 1859
  issue: 2
  year: 2007
  ident: 10.1016/j.energy.2010.07.043_bib37
  article-title: Locating multiple optima using particle swarm optimization
  publication-title: Applied Mathematics and Computation
  doi: 10.1016/j.amc.2006.12.066
  contributor:
    fullname: Brits
– year: 1991
  ident: 10.1016/j.energy.2010.07.043_bib26
  contributor:
    fullname: Davis
– ident: 10.1016/j.energy.2010.07.043_bib32
  doi: 10.1109/ICEC.1997.592270
– volume: 1
  start-page: 51
  issue: 1
  year: 1993
  ident: 10.1016/j.energy.2010.07.043_bib34
  article-title: A hierarchy of evolution programs: an experimental study
  publication-title: Evolutionary Computation
  doi: 10.1162/evco.1993.1.1.51
  contributor:
    fullname: Michalewicz
– ident: 10.1016/j.energy.2010.07.043_bib35
  doi: 10.1109/ICNN.1995.488968
– ident: 10.1016/j.energy.2010.07.043_bib41
  doi: 10.1109/ICEC.1998.699146
– year: 1975
  ident: 10.1016/j.energy.2010.07.043_bib22
  contributor:
    fullname: Holland
– year: 1999
  ident: 10.1016/j.energy.2010.07.043_bib25
  contributor:
    fullname: Michalewicz
– volume: 9
  start-page: 203
  year: 2005
  ident: 10.1016/j.energy.2010.07.043_bib4
  article-title: Sectoral energy consumption in Iran
  publication-title: Renewable and Sustainable Energy Reviews
  doi: 10.1016/j.rser.2004.03.002
  contributor:
    fullname: Hessari
– volume: 36
  start-page: 2637
  year: 2008
  ident: 10.1016/j.energy.2010.07.043_bib8
  article-title: A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2008.02.035
  contributor:
    fullname: Azadeh
– ident: 10.1016/j.energy.2010.07.043_bib42
  doi: 10.1007/BFb0040810
SSID ssj0005899
Score 2.4642327
Snippet This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on...
SourceID proquest
crossref
pascalfrancis
elsevier
SourceType Aggregation Database
Index Database
Publisher
StartPage 5223
SubjectTerms Applied sciences
Demand
Domestic
Economic data
Energy
Energy economics
Estimates
Exact sciences and technology
Exports
Fossil fuels and derived products
GA (genetic algorithm)
General, economic and professional studies
Genetic algorithms
Marketing
Mathematical models
Methodology. Modelling
Oil
Optimization
Projection
PSO (particle swarm optimization)
Title Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran
URI https://dx.doi.org/10.1016/j.energy.2010.07.043
https://search.proquest.com/docview/855719593
Volume 35
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELb6OICEEBQqtsDKBw7tId3Ej9g5rqqWLSsKolT0ZtmxU4KaZLXZqhIHfjvjxNlVhRASp0SRH7E_e2bseSH0TiTacjhUR6nwVzcul5GJizjimU2ZZcAzC3818PEinV2xD9f8egudDL4w3qwy0P6epnfUOnyZhNmcLMpycgm0F-QNRvwNNYODyjbaBXbkdbW70_P57GJj6SG7NJK-fOQrDB50nZmX61zsgo2XOI4Z_RuHerLQLcxb0Se8-IN2dwzp7Bl6GiRJPO1_9jnacvUeejQ4Grd7aP9048QGBcMubl-gn9ON1ho3Bf58-QkfLsKocXuvlxVugJRUwUfzCOva4vdTfAirzTs9Yn170yzL1ffqCK-DwLYYWrOu8mV96I5q3X5T3uKyxucwpJfo6uz068ksCjkYopxRtooK4aSJCWCYxIZroU2RZNxxG6fwWlhuaMEzCVsbGD2xRlpB01zLLI8ptSAb7aOduqndK4QN417PmlLjT3UxzZxLpSHSZToxhOQjFA3zrhZ9qA012KD9UD1OyuOkYqEApxESAzjqwZJRwA3-UXP8AMt1d4T6zPCEjxAewFWw3bwORdeuuWuV5Fz4eDz04L97f40ek7VNzBu0s1reubcg2azMGG0f_0rGYf365_zLt_lvRmb6Vg
link.rule.ids 314,780,784,4502,24116,27924,27925,45585,45679
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dT9swELcYPDBpmjY2RMfG_LAHeMjq-iNOHisEtAO6SYDEm2XHzhZEkqopQtpfv3PitEJomrS3yPJH7Dvfne373SH0RY60FXCojmLpr25clkSG5CQSqY255aAzc381cDmLJzf826243UDHPRbGu1UG2d_J9FZah5JhWM3hvCiGVyB7wd7g1N9QcziovEBbYA1IYO2t8fR8Mlt7eiRtGklfP_INegRd6-blWohd8PGSXwlnf9NQr-a6gXXLu4QXz2R3q5BO36DXwZLE4-5n36INV-2g7R5o3Oyg3ZM1iA0qhl3cvEO_x-tXa1zn-MfVd3w4D7PGzaNelLgGUVIGjOYR1pXFZ2N8CNzmQY9Y3_-sF8XyV3mEV0FgGwy9WVf6uj50R7nqvy7ucVHhKUzpPbo5Pbk-nkQhB0OUccaXUS5dYggFGo6IEVpqk49S4YQlMXzmVhiWizSBrQ2KnlqTWMniTCdpRhizYBvtos2qrtwewoYL_84aM-NPdYSlzsWJoYlL9chQmg1Q1K-7mnehNlTvg3anOjopTydFpAI6DZDsiaOesIwCbfCPlgdPaLkajjKfGZ6KAcI9cRVsN_-GoitXPzQqEUL6eDzsw3-P_hltT64vL9TFdHa-j17SlX_MR7S5XDy4T2DlLM1B4OI_mI36sA
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Application+of+PSO+%28particle+swarm+optimization%29+and+GA+%28genetic+algorithm%29+techniques+on+demand+estimation+of+oil+in+Iran&rft.jtitle=Energy+%28Oxford%29&rft.au=Assareh%2C+E&rft.au=Behrang%2C+MA&rft.au=Assari%2C+M+R&rft.au=Ghanbarzadeh%2C+A&rft.date=2010-12-01&rft.issn=0360-5442&rft.volume=35&rft.issue=12&rft.spage=5223&rft.epage=5229&rft_id=info:doi/10.1016%2Fj.energy.2010.07.043&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0360-5442&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0360-5442&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0360-5442&client=summon